m <- leaflet() %>%
addTiles() %>% # Add default OpenStreetMap map tiles
addMarkers(lng=-97.7431, lat=30.2672, popup="Austin, TX")
m # Print the map
m %>% addProviderTiles(providers$Stamen.Toner)
reg=lm(calls~fampov, data=TrainingData)
summary(reg)
##
## Call:
## lm(formula = calls ~ fampov, data = TrainingData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -355.5 -215.5 -42.9 101.4 657.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 204.7881 114.6450 1.786 0.09 .
## fampov 0.8979 0.1793 5.008 7.81e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 292.7 on 19 degrees of freedom
## Multiple R-squared: 0.569, Adjusted R-squared: 0.5463
## F-statistic: 25.08 on 1 and 19 DF, p-value: 7.805e-05
confint(reg)
## 2.5 % 97.5 %
## (Intercept) -35.1666160 444.742884
## fampov 0.5226503 1.273144
plot(reg)
reg=lm(calls~mfi2013, data=TestData)
summary(reg)
##
## Call:
## lm(formula = calls ~ mfi2013, data = TestData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1492.7 -789.4 -372.4 278.1 4391.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3167.93534 491.77186 6.442 3.04e-07 ***
## mfi2013 -0.02302 0.00591 -3.896 0.000469 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1211 on 32 degrees of freedom
## Multiple R-squared: 0.3217, Adjusted R-squared: 0.3005
## F-statistic: 15.18 on 1 and 32 DF, p-value: 0.0004686
confint(reg)
## 2.5 % 97.5 %
## (Intercept) 2166.22884605 4169.64182306
## mfi2013 -0.03506137 -0.01098666
plot(reg)
### Using plotly_build()
### Using plotly_build()